Raman spectroscopy performed using optical fibers, with excitation at 1064 nm and a dispersive detection scheme, was utilized to measure a selection of unifloral honeys produced in the Italian region of Calabria. The honey samples had three different botanical origins: chestnut, citrus, and acacia, respectively. A multivariate processing of the spectroscopic data enabled us to distinguish their botanical origin, and to build predictive models for quantifying important nutraceutic indicators such as the main sugars and potassium. Furthermore, the Raman spectra of chestnut honeys were compared with the taste profile measured by an electronic tongue, and a good correlation to bitter/savory taste was obtained. This experiment indicates the excellent potentials of Raman spectroscopy as an analytical tool for the nondestructive and rapid assessment of food-quality indicators.